Splitting network discovery payloads based on degree of relationships between nodes

ABSTRACT

An example embodiment may involve performing a discovery process to identify configuration items representing computing devices and applications in a managed network and determining that the configuration items exceed a threshold payload size. The embodiment may then involve generating a graph that represents the configuration items as nodes interconnected by unidirectional edges. The edges may represent respective associations between pairs of configuration items to which they connect, and the respective associations are classified either as weak associations that represent non-dependency relationships between a respective pair of nodes or as strong associations that represent dependency relationships between the respective pair of nodes. The embodiment may involve dividing the graph into overlapping sub-graphs based on the respective associations represented by the edges and, for each sub-graph, separately transmitting the configuration items defined therein to one or more server devices.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/655,284, filed on Jul. 20, 2017; the contents of which isincorporated herein in its entirety by reference.

BACKGROUND

Computer networks may involve dozens or hundreds of computing devices,each operating various software applications. Also referred to asconfiguration items, computing devices and applications may supportand/or facilitate higher-level or end-to-end services. As such, networktools can be used to discover and identify configuration items operatingwithin a network as well as the connectivity between configuration itemsin order to process and convey the current environment of the network.

In some applications, network tools may represent information about theconfiguration items as well as their associations using a set of webportals, services, and applications available to particular devices. Forinstance, configuration items information may be graphically representedas nodes with the connectivity of these configuration items representedas edges extending between nodes.

In some cases, however, the amount of information associated with theconfiguration items may become too large for the communication channelsused by the network tools. In particular, the communication channels maynot have the capacity to receive information pertaining to a payload ofa large number of configuration items discovered within a network.

SUMMARY

The embodiments herein improve upon transmission of large payloads ofconfiguration items discovered within a network by intelligentlydividing the payload into multiple portions for subsequent transferusing multiple transmissions. Particularly, a system may initiallydiscover configuration items in a managed network to determine thecurrent environment of the managed network. Upon determining that thepayload of discovered configuration items exceeds a threshold payloadsize, the system may generate a graph that represents each discoveredconfiguration item as a node and further includes edges between nodesrepresenting associations between pairs of the configuration items. Thesystem may utilize the graph to determine multiple sub-graphs based onthe degrees of relationships between the nodes. In doing so, the largepayload of configuration items that exceeded the threshold payload sizecan be divided in smaller portions and transmitted in a series via oneor more communication channels until the entire payload is completelytransmitted.

Accordingly, a first example embodiment may involve a proxy serverapplication disposed within a managed network. In particular, themanaged network includes computing devices configured to executeapplications. The embodiment may also involve one or more server devicesdisposed within a remote network management platform. The remote networkmanagement platform manages the managed network and the one or moreserver devices are configured to obtain information regarding thecomputing devices and the applications by way of the proxy serverapplication. The proxy server application is configured to perform adiscovery process to identify configuration items representing thecomputing devices and the applications, and determine that theconfiguration items exceed a threshold payload size. Based ondetermining that the configuration items exceed the threshold payloadsize, the proxy server application is configured to generate a graphthat represents the configuration items as nodes interconnected byunidirectional edges. The edges represent respective associationsbetween pairs of configuration items to which they connect. Therespective associations are classified either as weak associations thatrepresent non-dependency relationships between a respective pair ofnodes or as strong associations that represent dependency relationshipsbetween the respective pair of nodes. The proxy server application isfurther configured to divide the graph into overlapping sub-graphs basedon the respective associations represented by the edges. For instance, aparticular sub-graph is populated by recursively traversing and copyingnodes and edges from the graph as long as (i) nodes in the particularsub-graph represent fewer configuration items than the threshold payloadsize, and (ii) for any first node with an outgoing edge representing astrong association to a second node, the second node is in thesub-graph. As such, each sub-graph represents a portion of a payload ofthe configuration items. The proxy server application is furtherconfigured to separately transmit to the one or more server devices, foreach sub-graph, the configuration items defined therein.

In a second example embodiment, an article of manufacture may include anon-transitory computer-readable medium, having stored thereon programinstructions that, upon execution by a computing system, cause thecomputing system to perform operations in accordance with the firstexample embodiment.

In a third example embodiment, an example method may involve performingoperations in accordance with the first example embodiment.

In a fourth example embodiment, a computing system may include at leastone processor, as well as memory and program instructions. The programinstructions may be stored in the memory, and upon execution by the atleast one processor, cause the computing system to perform operations inaccordance with the first example embodiment.

In a fifth example embodiment, a system may include various means forcarrying out each of the operations of the first example embodiment.

These as well as other embodiments, aspects, advantages, andalternatives will become apparent to those of ordinary skill in the artby reading the following detailed description, with reference whereappropriate to the accompanying drawings. Further, this summary andother descriptions and figures provided herein are intended toillustrate embodiments by way of example only and, as such, thatnumerous variations are possible. For instance, structural elements andprocess steps can be rearranged, combined, distributed, eliminated, orotherwise changed, while remaining within the scope of the embodimentsas claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a schematic drawing of a computing device, inaccordance with example embodiments.

FIG. 2 illustrates a schematic drawing of a server device cluster, inaccordance with example embodiments.

FIG. 3 depicts a remote network management architecture, in accordancewith example embodiments.

FIG. 4 depicts a communication environment involving a remote networkmanagement architecture, in accordance with example embodiments.

FIG. 5A depicts another communication environment involving a remotenetwork management architecture, in accordance with example embodiments.

FIG. 5B is a flow chart, in accordance with example embodiments.

FIG. 6A depicts a graph of discovered configuration items, in accordancewith example embodiments.

FIG. 6B depicts a sub-graph formed based on the graph of discoveredconfiguration items, in accordance with example embodiments.

FIG. 6C depicts associations extending from a particular node in thesub-graph formed based on the graph of discovered configuration items,in accordance with example embodiments.

FIG. 6D depicts another sub-graph formed based on the graph ofdiscovered configuration items, in accordance with example embodiments.

FIG. 6E depicts an additional sub-graph formed based on the graph ofdiscovered configuration items, in accordance with example embodiments.

FIG. 6F depicts another sub-graph formed based another particular nodein the graph of discovered configuration items, in accordance withexample embodiments.

FIG. 6G depicts a depth-first search of the graph of discoveredconfiguration items, in accordance with example embodiments.

FIG. 7 is a flow chart, in accordance with example embodiments.

DETAILED DESCRIPTION

Example methods, devices, and systems are described herein. It should beunderstood that the words “example” and “exemplary” are used herein tomean “serving as an example, instance, or illustration.” Any embodimentor feature described herein as being an “example” or “exemplary” is notnecessarily to be construed as preferred or advantageous over otherembodiments or features unless stated as such. Thus, other embodimentscan be utilized and other changes can be made without departing from thescope of the subject matter presented herein.

Accordingly, the example embodiments described herein are not meant tobe limiting. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe figures, can be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations. For example, theseparation of features into “client” and “server” components may occurin a number of ways.

Further, unless context suggests otherwise, the features illustrated ineach of the figures may be used in combination with one another. Thus,the figures should be generally viewed as component aspects of one ormore overall embodiments, with the understanding that not allillustrated features are necessary for each embodiment.

Additionally, any enumeration of elements, blocks, or steps in thisspecification or the claims is for purposes of clarity. Thus, suchenumeration should not be interpreted to require or imply that theseelements, blocks, or steps adhere to a particular arrangement or arecarried out in a particular order.

Introduction

A large enterprise is a complex entity with many interrelatedoperations. Some of these are found across the enterprise, such as humanresources (HR), supply chain, information technology (IT), and finance.However, each enterprise also has its own unique operations that provideessential capabilities and/or create competitive advantages.

To support widely-implemented operations, enterprises typically useoff-the-shelf software applications, such as customer relationshipmanagement (CRM) and human capital management (HCM) packages. However,they may also need custom software applications to meet their own uniquerequirements. A large enterprise often has dozens or hundreds of thesecustom software applications. Nonetheless, the advantages provided bythe embodiments herein are not limited to large enterprises and may beapplicable to an enterprise, or any other type of organization, of anysize.

Many such software applications are developed by individual departmentswithin the enterprise. These range from simple spreadsheets tocustom-built software tools and databases. But the proliferation ofsiloed custom software applications has numerous disadvantages. Itnegatively impacts an enterprise's ability to run and grow its business,innovate, and meet regulatory requirements. The enterprise may find itdifficult to integrate, streamline and enhance its operations due tolack of a single system that unifies its subsystems and data.

To efficiently create custom applications, enterprises would benefitfrom a remotely-hosted application platform that eliminates unnecessarydevelopment complexity. The goal of such a platform would be to reducetime-consuming, repetitive application development tasks so thatsoftware engineers and individuals in other roles can focus ondeveloping unique, high-value features.

In order to achieve this goal, the concept of Application Platform as aService (aPaaS) is introduced, to intelligently automate workflowsthroughout the enterprise. An aPaaS system is hosted remotely from theenterprise, but may access data, applications, and services within theenterprise by way of secure connections. Such an aPaaS system may have anumber of advantageous capabilities and characteristics. Theseadvantages and characteristics may be able to improve the enterprise'soperations and workflow for IT, HR, CRM, customer service, applicationdevelopment, and security.

The aPaaS system may support development and execution ofmodel-view-controller (MVC) applications. MVC applications divide theirfunctionality into three interconnected parts (model, view, andcontroller) in order to isolate representations of information from themanner in which the information is presented to the user, therebyallowing for efficient code reuse and parallel development. Theseapplications may be web-based, and offer, create, read, update, delete(CRUD) capabilities. This allows new applications to be built on acommon application infrastructure.

The aPaaS system may support standardized application components, suchas a standardized set of widgets for graphical user interface (GUI)development. In this way, applications built using the aPaaS system havea common look and feel. Other software components and modules may bestandardized as well. In some cases, this look and feel can be brandedor skinned with an enterprise's custom logos and/or color schemes.

The aPaaS system may support the ability to configure the behavior ofapplications using metadata. This allows application behaviors to berapidly adapted to meet specific needs. Such an approach reducesdevelopment time and increases flexibility. Further, the aPaaS systemmay support GUI tools that facilitate metadata creation and management,thus reducing errors in the metadata.

The aPaaS system may support clearly-defined interfaces betweenapplications, so that software developers can avoid unwantedinter-application dependencies. Thus, the aPaaS system may implement aservice layer in which persistent state information and other data isstored.

The aPaaS system may support a rich set of integration features so thatthe applications thereon can interact with legacy applications andthird-party applications. For instance, the aPaaS system may support acustom employee-onboarding system that integrates with legacy HR, IT,and accounting systems.

The aPaaS system may support enterprise-grade security. Furthermore,since the aPaaS system may be remotely hosted, it should also utilizesecurity procedures when it interacts with systems in the enterprise orthird-party networks and services hosted outside of the enterprise. Forexample, the aPaaS system may be configured to share data amongst theenterprise and other parties to detect and identify common securitythreats.

Other features, functionality, and advantages of an aPaaS system mayexist. This description is for purpose of example and is not intended tobe limiting.

As an example of the aPaaS development process, a software developer maybe tasked to create a new application using the aPaaS system. First, thedeveloper may define the data model, which specifies the types of datathat the application uses and the relationships therebetween. Then, viaa GUI of the aPaaS system, the developer enters (e.g., uploads) the datamodel. The aPaaS system automatically creates all of the correspondingdatabase tables, fields, and relationships, which can then be accessedvia an object-oriented services layer.

In addition, the aPaaS system can also build a fully-functional MVCapplication with client-side interfaces and server-side CRUD logic. Thisgenerated application may serve as the basis of further development forthe user. Advantageously, the developer does not have to spend a largeamount of time on basic application functionality. Further, since theapplication may be web-based, it can be accessed from anyInternet-enabled client device. Alternatively or additionally, a localcopy of the application may be able to be accessed, for instance, whenInternet service is not available.

The aPaaS system may also support a rich set of pre-definedfunctionality that can be added to applications. These features includesupport for searching, email, templating, workflow design, reporting,analytics, social media, scripting, mobile-friendly output, andcustomized GUIs.

The following embodiments describe architectural and functional aspectsof example aPaaS systems, as well as the features and advantagesthereof.

II. Example Computing Devices and Cloud-Based Computing Environments

FIG. 1 is a simplified block diagram exemplifying a computing device100, illustrating some of the components that could be included in acomputing device arranged to operate in accordance with the embodimentsherein. Computing device 100 could be a client device (e.g., a deviceactively operated by a user), a server device (e.g., a device thatprovides computational services to client devices), or some other typeof computational platform. Some server devices may operate as clientdevices from time to time in order to perform particular operations, andsome client devices may incorporate server features.

In this example, computing device 100 includes processor 102, memory104, network interface 106, and an input/output unit 108, all of whichmay be coupled by a system bus 110 or a similar mechanism. In someembodiments, computing device 100 may include other components and/orperipheral devices (e.g., detachable storage, printers, and so on).

Processor 102 may be one or more of any type of computer processingelement, such as a central processing unit (CPU), a co-processor (e.g.,a mathematics, graphics, or encryption co-processor), a digital signalprocessor (DSP), a network processor, and/or a form of integratedcircuit or controller that performs processor operations. In some cases,processor 102 may be one or more single-core processors. In other cases,processor 102 may be one or more multi-core processors with multipleindependent processing units. Processor 102 may also include registermemory for temporarily storing instructions being executed and relateddata, as well as cache memory for temporarily storing recently-usedinstructions and data.

Memory 104 may be any form of computer-usable memory, including but notlimited to random access memory (RAM), read-only memory (ROM), andnon-volatile memory (e.g., flash memory, hard disk drives, solid statedrives, compact discs (CDs), digital video discs (DVDs), and/or tapestorage). Thus, memory 104 represents both main memory units, as well aslong-term storage. Other types of memory may include biological memory.

Memory 104 may store program instructions and/or data on which programinstructions may operate. By way of example, memory 104 may store theseprogram instructions on a non-transitory, computer-readable medium, suchthat the instructions are executable by processor 102 to carry out anyof the methods, processes, or operations disclosed in this specificationor the accompanying drawings.

As shown in FIG. 1, memory 104 may include firmware 104A, kernel 104B,and/or applications 104C. Firmware 104A may be program code used to bootor otherwise initiate some or all of computing device 100. Kernel 104Bmay be an operating system, including modules for memory management,scheduling and management of processes, input/output, and communication.Kernel 104B may also include device drivers that allow the operatingsystem to communicate with the hardware modules (e.g., memory units,networking interfaces, ports, and busses), of computing device 100.Applications 104C may be one or more user-space software programs, suchas web browsers or email clients, as well as any software libraries usedby these programs. Memory 104 may also store data used by these andother programs and applications.

Network interface 106 may take the form of one or more wirelineinterfaces, such as Ethernet (e.g., Fast Ethernet, Gigabit Ethernet, andso on). Network interface 106 may also support communication over one ormore non-Ethernet media, such as coaxial cables or power lines, or overwide-area media, such as Synchronous Optical Networking (SONET) ordigital subscriber line (DSL) technologies. Network interface 106 mayadditionally take the form of one or more wireless interfaces, such asIEEE 802.11 (Wifi), BLUETOOTH®, global positioning system (GPS), or awide-area wireless interface. However, other forms of physical layerinterfaces and other types of standard or proprietary communicationprotocols may be used over network interface 106. Furthermore, networkinterface 106 may comprise multiple physical interfaces. For instance,some embodiments of computing device 100 may include Ethernet,BLUETOOTH®, and Wifi interfaces.

Input/output unit 108 may facilitate user and peripheral deviceinteraction with example computing device 100. Input/output unit 108 mayinclude one or more types of input devices, such as a keyboard, a mouse,a touch screen, and so on. Similarly, input/output unit 108 may includeone or more types of output devices, such as a screen, monitor, printer,and/or one or more light emitting diodes (LEDs). Additionally oralternatively, computing device 100 may communicate with other devicesusing a universal serial bus (USB) or high-definition multimediainterface (HDMI) port interface, for example.

In some embodiments, one or more instances of computing device 100 maybe deployed to support an aPaaS architecture. The exact physicallocation, connectivity, and configuration of these computing devices maybe unknown and/or unimportant to client devices. Accordingly, thecomputing devices may be referred to as “cloud-based” devices that maybe housed at various remote data center locations.

FIG. 2 depicts a cloud-based server cluster 200 in accordance withexample embodiments. In FIG. 2, operations of a computing device (e.g.,computing device 100) may be distributed between server devices 202,data storage 204, and routers 206, all of which may be connected bylocal cluster network 208. The number of server devices 202, datastorages 204, and routers 206 in server cluster 200 may depend on thecomputing task(s) and/or applications assigned to server cluster 200.

For example, server devices 202 can be configured to perform variouscomputing tasks of computing device 100. Thus, computing tasks can bedistributed among one or more of server devices 202. To the extent thatthese computing tasks can be performed in parallel, such a distributionof tasks may reduce the total time to complete these tasks and return aresult. For purpose of simplicity, both server cluster 200 andindividual server devices 202 may be referred to as a “server device.”This nomenclature should be understood to imply that one or moredistinct server devices, data storage devices, and cluster routers maybe involved in server device operations.

Data storage 204 may be data storage arrays that include drive arraycontrollers configured to manage read and write access to groups of harddisk drives and/or solid state drives. The drive array controllers,alone or in conjunction with server devices 202, may also be configuredto manage backup or redundant copies of the data stored in data storage204 to protect against drive failures or other types of failures thatprevent one or more of server devices 202 from accessing units ofcluster data storage 204. Other types of memory aside from drives may beused.

Routers 206 may include networking equipment configured to provideinternal and external communications for server cluster 200. Forexample, routers 206 may include one or more packet-switching and/orrouting devices (including switches and/or gateways) configured toprovide (i) network communications between server devices 202 and datastorage 204 via cluster network 208, and/or (ii) network communicationsbetween the server cluster 200 and other devices via communication link210 to network 212.

Additionally, the configuration of cluster routers 206 can be based atleast in part on the data communication requirements of server devices202 and data storage 204, the latency and throughput of the localcluster network 208, the latency, throughput, and cost of communicationlink 210, and/or other factors that may contribute to the cost, speed,fault-tolerance, resiliency, efficiency and/or other design goals of thesystem architecture.

As a possible example, data storage 204 may include any form ofdatabase, such as a structured query language (SQL) database. Varioustypes of data structures may store the information in such a database,including but not limited to tables, arrays, lists, trees, and tuples.Furthermore, any databases in data storage 204 may be monolithic ordistributed across multiple physical devices.

Server devices 202 may be configured to transmit data to and receivedata from cluster data storage 204. This transmission and retrieval maytake the form of SQL queries or other types of database queries, and theoutput of such queries, respectively. Additional text, images, video,and/or audio may be included as well. Furthermore, server devices 202may organize the received data into web page representations. Such arepresentation may take the form of a markup language, such as thehypertext markup language (HTML), the extensible markup language (XML),or some other standardized or proprietary format. Moreover, serverdevices 202 may have the capability of executing various types ofcomputerized scripting languages, such as but not limited to Perl,Python, PHP Hypertext Preprocessor (PHP), Active Server Pages (ASP),JavaScript, and so on. Computer program code written in these languagesmay facilitate the providing of web pages to client devices, as well asclient device interaction with the web pages.

III. Example Remote Network Management Architecture

FIG. 3 depicts a remote network management architecture, in accordancewith example embodiments. This architecture includes three maincomponents, managed network 300, remote network management platform 320,and third-party networks 340, all connected by way of Internet 350.

Managed network 300 may be, for example, an enterprise network used by abusiness for computing and communications tasks, as well as storage ofdata. Thus, managed network 300 may include various client devices 302,server devices 304, routers 306, virtual machines 308, firewall 310,and/or proxy servers 312. Client devices 302 may be embodied bycomputing device 100, server devices 304 may be embodied by computingdevice 100 or server cluster 200, and routers 306 may be any type ofrouter, switch, or gateway.

Virtual machines 308 may be embodied by one or more of computing device100 or server cluster 200. In general, a virtual machine is an emulationof a computing system, and mimics the functionality (e.g., processor,memory, and communication resources) of a physical computer. Onephysical computing system, such as server cluster 200, may support up tothousands of individual virtual machines. In some embodiments, virtualmachines 308 may be managed by a centralized server device orapplication that facilitates allocation of physical computing resourcesto individual virtual machines, as well as performance and errorreporting. Enterprises often employ virtual machines in order toallocate computing resources in an efficient, as needed fashion.Providers of virtualized computing systems include VMWARE® andMICROSOFT®.

Firewall 310 may be one or more specialized routers or server devicesthat protect managed network 300 from unauthorized attempts to accessthe devices, applications, and services therein, while allowingauthorized communication that is initiated from managed network 300.Firewall 310 may also provide intrusion detection, web filtering, virusscanning, application-layer gateways, and other applications orservices. In some embodiments not shown in FIG. 3, managed network 300may include one or more virtual private network (VPN) gateways withwhich it communicates with remote network management platform 320 (seebelow).

Managed network 300 may also include one or more proxy servers 312. Anembodiment of proxy servers 312 may be a server device that facilitatescommunication and movement of data between managed network 300, remotenetwork management platform 320, and third-party networks 340. Inparticular, proxy servers 312 may be able to establish and maintainsecure communication sessions with one or more customer instances ofremote network management platform 320. By way of such a session, remotenetwork management platform 320 may be able to discover and manageaspects of the architecture and configuration of managed network 300 andits components. Possibly with the assistance of proxy servers 312,remote network management platform 320 may also be able to discover andmanage aspects of third-party networks 340 that are used by managednetwork 300.

Firewalls, such as firewall 310, typically deny all communicationsessions that are incoming by way of Internet 350, unless such a sessionwas ultimately initiated from behind the firewall (i.e., from a deviceon managed network 300) or the firewall has been explicitly configuredto support the session. By placing proxy servers 312 behind firewall 310(e.g., within managed network 300 and protected by firewall 310), proxyservers 312 may be able to initiate these communication sessions throughfirewall 310. Thus, firewall 310 might not have to be specificallyconfigured to support incoming sessions from remote network managementplatform 320, thereby avoiding potential security risks to managednetwork 300.

In some cases, managed network 300 may consist of a few devices and asmall number of networks. In other deployments, managed network 300 mayspan multiple physical locations and include hundreds of networks andhundreds of thousands of devices. Thus, the architecture depicted inFIG. 3 is capable of scaling up or down by orders of magnitude.

Furthermore, depending on the size, architecture, and connectivity ofmanaged network 300, a varying number of proxy servers 312 may bedeployed therein. For example, each one of proxy servers 312 may beresponsible for communicating with remote network management platform320 regarding a portion of managed network 300. Alternatively oradditionally, sets of two or more proxy servers may be assigned to sucha portion of managed network 300 for purposes of load balancing,redundancy, and/or high availability.

Remote network management platform 320 is a hosted environment thatprovides aPaaS services to users, particularly to the operators ofmanaged network 300. These services may take the form of web-basedportals, for instance. Thus, a user can securely access remote networkmanagement platform 320 from, for instance, client devices 302, orpotentially from a client device outside of managed network 300. By wayof the web-based portals, users may design, test, and deployapplications, generate reports, view analytics, and perform other tasks.

As shown in FIG. 3, remote network management platform 320 includes fourcustomer instances 322, 324, 326, and 328. Each of these instances mayrepresent a set of web portals, services, and applications (e.g., awholly-functioning aPaaS system) available to a particular customer. Insome cases, a single customer may use multiple customer instances. Forexample, managed network 300 may be an enterprise customer of remotenetwork management platform 320, and may use customer instances 322,324, and 326. The reason for providing multiple instances to onecustomer is that the customer may wish to independently develop, test,and deploy its applications and services. Thus, customer instance 322may be dedicated to application development related to managed network300, customer instance 324 may be dedicated to testing theseapplications, and customer instance 326 may be dedicated to the liveoperation of tested applications and services.

The multi-instance architecture of remote network management platform320 is in contrast to conventional multi-tenant architectures, overwhich multi-instance architectures have several advantages. Inmulti-tenant architectures, data from different customers (e.g.,enterprises) are comingled in a single database. While these customers'data are separate from one another, the separation is enforced by thesoftware that operates the single database. As a consequence, a securitybreach in this system may impact all customers' data, creatingadditional risk, especially for entities subject to governmental,healthcare, and/or financial regulation. Furthermore, any databaseoperations that impact one customer will likely impact all customerssharing that database. Thus, if there is an outage due to hardware orsoftware errors, this outage affects all such customers. Likewise, ifthe database is to be upgraded to meet the needs of one customer, itwill be unavailable to all customers during the upgrade process. Often,such maintenance windows will be long, due to the size of the shareddatabase.

In contrast, the multi-instance architecture provides each customer withits own database in a dedicated computing instance. This preventscomingling of customer data, and allows each instance to beindependently managed. For example, when one customer's instanceexperiences an outage due to errors or an upgrade, other customerinstances are not impacted. Maintenance down time is limited because thedatabase only contains one customer's data. Further, the simpler designof the multi-instance architecture allows redundant copies of eachcustomer database and instance to be deployed in a geographicallydiverse fashion. This facilitates high availability, where the liveversion of the customer's instance can be moved when faults are detectedor maintenance is being performed.

In order to support multiple customer instances in an efficient fashion,remote network management platform 320 may implement a plurality ofthese instances on a single hardware platform. For example, when theaPaaS system is implemented on a server cluster such as server cluster200, it may operate a virtual machine that dedicates varying amounts ofcomputational, storage, and communication resources to instances. Butfull virtualization of server cluster 200 might not be necessary, andother mechanisms may be used to separate instances. In some examples,each instance may have a dedicated account and one or more dedicateddatabases on server cluster 200. Alternatively, customer instance 322may span multiple physical devices.

In some cases, a single server cluster of remote network managementplatform 320 may support multiple independent enterprises. Furthermore,as described below, remote network management platform 320 may includemultiple server clusters deployed in geographically diverse data centersin order to facilitate load balancing, redundancy, and/or highavailability.

Third-party networks 340 may be remote server devices (e.g., a pluralityof server clusters such as server cluster 200) that can be used foroutsourced computational, data storage, communication, and servicehosting operations. These servers may be virtualized (i.e., the serversmay be virtual machines). Examples of third-party networks 340 mayinclude AMAZON WEB SERVICES® and MICROSOFT® Azure. Like remote networkmanagement platform 320, multiple server clusters supporting third-partynetworks 340 may be deployed at geographically diverse locations forpurposes of load balancing, redundancy, and/or high availability.

Managed network 300 may use one or more of third-party networks 340 todeploy applications and services to its clients and customers. Forinstance, if managed network 300 provides online music streamingservices, third-party networks 340 may store the music files and provideweb interface and streaming capabilities. In this way, the enterprise ofmanaged network 300 does not have to build and maintain its own serversfor these operations.

Remote network management platform 320 may include modules thatintegrate with third-party networks 340 to expose virtual machines andmanaged services therein to managed network 300. The modules may allowusers to request virtual resources and provide flexible reporting forthird-party networks 340. In order to establish this functionality, auser from managed network 300 might first establish an account withthird-party networks 340, and request a set of associated resources.Then, the user may enter the account information into the appropriatemodules of remote network management platform 320. These modules maythen automatically discover the manageable resources in the account, andalso provide reports related to usage, performance, and billing.

Internet 350 may represent a portion of the global Internet. However,Internet 350 may alternatively represent a different type of network,such as a private wide-area or local-area packet-switched network.

FIG. 4 further illustrates the communication environment between managednetwork 300 and customer instance 322, and introduces additionalfeatures and alternative embodiments. In FIG. 4, customer instance 322is replicated across data centers 400A and 400B. These data centers maybe geographically distant from one another, perhaps in different citiesor different countries. Each data center includes support equipment thatfacilitates communication with managed network 300, as well as remoteusers.

In data center 400A, network traffic to and from external devices flowseither through VPN gateway 402A or firewall 404A. VPN gateway 402A maybe peered with VPN gateway 412 of managed network 300 by way of asecurity protocol such as Internet Protocol Security (IPSEC). Firewall404A may be configured to allow access from authorized users, such asuser 414 and remote user 416, and to deny access to unauthorized users.By way of firewall 404A, these users may access customer instance 322,and possibly other customer instances. Load balancer 406A may be used todistribute traffic amongst one or more physical or virtual serverdevices that host customer instance 322. Load balancer 406A may simplifyuser access by hiding the internal configuration of data center 400A,(e.g., customer instance 322) from client devices. For instance, ifcustomer instance 322 includes multiple physical or virtual computingdevices that share access to multiple databases, load balancer 406A maydistribute network traffic and processing tasks across these computingdevices and databases so that no one computing device or database issignificantly busier than the others. In some embodiments, customerinstance 322 may include VPN gateway 402A, firewall 404A, and loadbalancer 406A.

Data center 400B may include its own versions of the components in datacenter 400A. Thus, VPN gateway 402B, firewall 404B, and load balancer406B may perform the same or similar operations as VPN gateway 402A,firewall 404A, and load balancer 406A, respectively. Further, by way ofreal-time or near-real-time database replication and/or otheroperations, customer instance 322 may exist simultaneously in datacenters 400A and 400B.

Data centers 400A and 400B as shown in FIG. 4 may facilitate redundancyand high availability. In the configuration of FIG. 4, data center 400Ais active and data center 400B is passive. Thus, data center 400A isserving all traffic to and from managed network 300, while the versionof customer instance 322 in data center 400B is being updated innear-real-time. Other configurations, such as one in which both datacenters are active, may be supported.

Should data center 400A fail in some fashion or otherwise becomeunavailable to users, data center 400B can take over as the active datacenter. For example, domain name system (DNS) servers that associate adomain name of customer instance 322 with one or more Internet Protocol(IP) addresses of data center 400A may re-associate the domain name withone or more IP addresses of data center 400B. After this re-associationcompletes (which may take less than one second or several seconds),users may access customer instance 322 by way of data center 400B.

FIG. 4 also illustrates a possible configuration of managed network 300.As noted above, proxy servers 312 and user 414 may access customerinstance 322 through firewall 310. Proxy servers 312 may also accessconfiguration items 410. In FIG. 4, configuration items 410 may refer toany or all of client devices 302, server devices 304, routers 306, andvirtual machines 308, any applications or services executing thereon, aswell as relationships between devices, applications, and services. Thus,the term “configuration items” may be shorthand for any physical orvirtual device, or any application or service remotely discoverable ormanaged by customer instance 322, or relationships between discovereddevices, applications, and services. Configuration items may berepresented in a configuration management database (CMDB) of customerinstance 322.

As noted above, VPN gateway 412 may provide a dedicated VPN to VPNgateway 402A. Such a VPN may be helpful when there is a significantamount of traffic between managed network 300 and customer instance 322,or security policies otherwise suggest or require use of a VPN betweenthese sites. In some embodiments, any device in managed network 300and/or customer instance 322 that directly communicates via the VPN isassigned a public IP address. Other devices in managed network 300and/or customer instance 322 may be assigned private IP addresses (e.g.,IP addresses selected from the 10.0.0.0-10.255.255.255 or192.168.0.0-192.168.255.255 ranges, represented in shorthand as subnets10.0.0.0/8 and 192.168.0.0/16, respectively).

IV. Example Device, Application, and Service Discovery

In order for remote network management platform 320 to administer thedevices, applications, and services of managed network 300, remotenetwork management platform 320 may first determine what devices arepresent in managed network 300, the configurations and operationalstatuses of these devices, and the applications and services provided bythe devices, and well as the relationships between discovered devices,applications, and services. As noted above, each device, application,service, and relationship may be referred to as a configuration item.The process of defining configuration items within managed network 300is referred to as discovery, and may be facilitated at least in part byproxy servers 312.

For purpose of the embodiments herein, an “application” may refer to oneor more processes, threads, programs, client modules, server modules, orany other software that executes on a device or group of devices. A“service” may refer to a high-level capability provided by multipleapplications executing on one or more devices working in conjunctionwith one another. For example, a high-level web service may involvemultiple web application server threads executing on one device andaccessing information from a database application that executes onanother device.

FIG. 5A provides a logical depiction of how configuration items can bediscovered, as well as how information related to discoveredconfiguration items can be stored. For sake of simplicity, remotenetwork management platform 320, third-party networks 340, and Internet350 are not shown.

In FIG. 5A, CMDB 500 and task list 502 are stored within customerinstance 322. Customer instance 322 may transmit discovery commands toproxy servers 312. In response, proxy servers 312 may transmit probes tovarious devices, applications, and services in managed network 300.These devices, applications, and services may transmit responses toproxy servers 312, and proxy servers 312 may then provide informationregarding discovered configuration items to CMDB 500 for storagetherein. Configuration items stored in CMDB 500 represent theenvironment of managed network 300.

Task list 502 represents a list of activities that proxy servers 312 areto perform on behalf of customer instance 322. As discovery takes place,task list 502 is populated. Proxy servers 312 repeatedly query task list502, obtain the next task therein, and perform this task until task list502 is empty or another stopping condition has been reached.

To facilitate discovery, proxy servers 312 may be configured withinformation regarding one or more subnets in managed network 300 thatare reachable by way of proxy servers 312. For instance, proxy servers312 may be given the IP address range 192.168.0/24 as a subnet. Then,customer instance 322 may store this information in CMDB 500 and placetasks in task list 502 for discovery of devices at each of theseaddresses.

FIG. 5A also depicts devices, applications, and services in managednetwork 300 as configuration items 504, 506, 508, 510, and 512. As notedabove, these configuration items represent a set of physical and/orvirtual devices (e.g., client devices, server devices, routers, orvirtual machines), applications executing thereon (e.g., webservers,email servers, databases, or storage arrays), relationshipstherebetween, as well as services that involve multiple individualconfiguration items.

Placing the tasks in task list 502 may trigger or otherwise cause proxyservers 312 to begin discovery. Alternatively or additionally, discoverymay be manually triggered or automatically triggered based on triggeringevents (e.g., discovery may automatically begin once per day at aparticular time).

In general, discovery may proceed in four logical phases: scanning,classification, identification, and exploration. Each phase of discoveryinvolves various types of probe messages being transmitted by proxyservers 312 to one or more devices in managed network 300. The responsesto these probes may be received and processed by proxy servers 312, andrepresentations thereof may be transmitted to CMDB 500. Thus, each phasecan result in more configuration items being discovered and stored inCMDB 500.

In the scanning phase, proxy servers 312 may probe each IP address inthe specified range of IP addresses for open Transmission ControlProtocol (TCP) and/or User Datagram Protocol (UDP) ports to determinethe general type of device. The presence of such open ports at an IPaddress may indicate that a particular application is operating on thedevice that is assigned the IP address, which in turn may identify theoperating system used by the device. For example, if TCP port 135 isopen, then the device is likely executing a WINDOWS® operating system.Similarly, if TCP port 22 is open, then the device is likely executing aUNIX® operating system, such as LINUX®. If UDP port 161 is open, thenthe device may be able to be further identified through the SimpleNetwork Management Protocol (SNMP). Other possibilities exist. Once thepresence of a device at a particular IP address and its open ports havebeen discovered, these configuration items are saved in CMDB 500.

In the classification phase, proxy servers 312 may further probe eachdiscovered device to determine the version of its operating system. Theprobes used for a particular device are based on information gatheredabout the devices during the scanning phase. For example, if a device isfound with TCP port 22 open, a set of UNIX®-specific probes may be used.Likewise, if a device is found with TCP port 135 open, a set ofWINDOWS®-specific probes may be used. For either case, an appropriateset of tasks may be placed in task list 502 for proxy servers 312 tocarry out. These tasks may result in proxy servers 312 logging on, orotherwise accessing information from the particular device. Forinstance, if TCP port 22 is open, proxy servers 312 may be instructed toinitiate a Secure Shell (SSH) connection to the particular device andobtain information about the operating system thereon from particularlocations in the file system. Based on this information, the operatingsystem may be determined. As an example, a UNIX® device with TCP port 22open may be classified as AIX®, HPUX, LINUX®, MACOS®, or SOLARIS®. Thisclassification information may be stored as one or more configurationitems in CMDB 500.

In the identification phase, proxy servers 312 may determine specificdetails about a classified device. The probes used during this phase maybe based on information gathered about the particular devices during theclassification phase. For example, if a device was classified as LINUX®,as a set of LINUX®-specific probes may be used. Likewise if a device wasclassified as WINDOWS® 2012, as a set of WINDOWS®-2012-specific probesmay be used. As was the case for the classification phase, anappropriate set of tasks may be placed in task list 502 for proxyservers 312 to carry out. These tasks may result in proxy servers 312reading information from the particular device, such as basicinput/output system (BIOS) information, serial numbers, networkinterface information, media access control address(es) assigned tothese network interface(s), IP address(es) used by the particular deviceand so on. This identification information may be stored as one or moreconfiguration items in CMDB 500.

In the exploration phase, proxy servers 312 may determine furtherdetails about the operational state of a classified device. The probesused during this phase may be based on information gathered about theparticular devices during the classification phase and/or theidentification phase. Again, an appropriate set of tasks may be placedin task list 502 for proxy servers 312 to carry out. These tasks mayresult in proxy servers 312 reading additional information from theparticular device, such as processor information, memory information,lists of running processes (applications), and so on. Once more, thediscovered information may be stored as one or more configuration itemsin CMDB 500.

Running discovery on a network device, such as a router, may utilizeSNMP. Instead of or in addition to determining a list of runningprocesses or other application-related information, discovery maydetermine additional subnets known to the router and the operationalstate of the router's network interfaces (e.g., active, inactive, queuelength, number of packets dropped, etc.). The IP addresses of theadditional subnets may be candidates for further discovery procedures.Thus, discovery may progress iteratively or recursively.

Once discovery completes, a snapshot representation of each discovereddevice, application, and service is available in CMDB 500. For example,after discovery, operating system version, hardware configuration andnetwork configuration details for client devices, server devices, androuters in managed network 300, as well as applications executingthereon, may be stored. This collected information may be presented to auser in various ways to allow the user to view the hardware compositionand operational status of devices, as well as the characteristics ofservices that span multiple devices and applications.

Furthermore, CMDB 500 may include entries regarding dependencies andrelationships between configuration items. More specifically, anapplication that is executing on a particular server device, as well asthe services that rely on this application, may be represented as suchin CMDB 500. For instance, suppose that a database application isexecuting on a server device, and that this database application is usedby a new employee onboarding service as well as a payroll service. Thus,if the server device is taken out of operation for maintenance, it isclear that the employee onboarding service and payroll service will beimpacted. Likewise, the dependencies and relationships betweenconfiguration items may be able to represent the services impacted whena particular router fails.

In general, dependencies and relationships between configuration itemsbe displayed on a web-based interface and represented in a hierarchicalfashion. Thus, adding, changing, or removing such dependencies andrelationships may be accomplished by way of this interface.

Furthermore, users from managed network 300 may develop workflows thatallow certain coordinated activities to take place across multiplediscovered devices. For instance, an IT workflow might allow the user tochange the common administrator password to all discovered LINUX®devices in single operation.

In order for discovery to take place in the manner described above,proxy servers 312, CMDB 500, and/or one or more credential stores may beconfigured with credentials for one or more of the devices to bediscovered. Credentials may include any type of information needed inorder to access the devices. These may include userid/password pairs,certificates, and so on. In some embodiments, these credentials may bestored in encrypted fields of CMDB 500. Proxy servers 312 may containthe decryption key for the credentials so that proxy servers 312 can usethese credentials to log on to or otherwise access devices beingdiscovered.

The discovery process is depicted as a flow chart in FIG. 5B. At block520, the task list in the customer instance is populated, for instance,with a range of IP addresses. At block 522, the scanning phase takesplace. Thus, the proxy servers probe the IP addresses for devices usingthese IP addresses, and attempt to determine the operating systems thatare executing on these devices. At block 524, the classification phasetakes place. The proxy servers attempt to determine the operating systemversion of the discovered devices. At block 526, the identificationphase takes place. The proxy servers attempt to determine the hardwareand/or software configuration of the discovered devices. At block 528,the exploration phase takes place. The proxy servers attempt todetermine the operational state and applications executing on thediscovered devices. At block 530, further editing of the configurationitems representing the discovered devices and applications may takeplace. This editing may be automated and/or manual in nature.

The blocks represented in FIG. 5B are for purpose of example. Discoverymay be a highly configurable procedure that can have more or fewerphases, and the operations of each phase may vary. In some cases, one ormore phases may be customized, or may otherwise deviate from theexemplary descriptions above.

V. Example Discovered Payload Division System and Process

As indicated above, in order for remote network management platform 320to administer the devices, applications, and services of managed network300, remote management platform 320 may initiate a discovery process,such as the discovery process described with regard to FIGS. 5A-5B.Particularly, remote network management platform 320 may utilize one ormore proxy servers 312 to discover and identify configuration items 410(e.g., devices, applications, and services) in managed network 300 aswell information about configuration items 410, such as the operationalstatus of each configuration item and the associations betweenconfiguration items 410. The proxy servers 312 may transmit informationregarding discovered configuration items via secured communicationsessions with one or more customer instances 322, 324, 326, and 328 ofremote management platform 320. As a result, the discovery process mayenable remote network management platform 320 to access and representthe current environment of managed network 300 to one or more particulardevices.

In some instances, the discovery process may result in the discovery andidentification of a large payload of configuration items. In particular,the proxy servers 312 may determine that the payload of discoveredconfigurations items exceed a threshold payload size that represents theamount of information that the communication channel(s) are able totransfer between the proxy servers 312 and one or more servers of remotenetwork management platform 320.

In order to transfer the large payload of configuration items despitethe size of the payload exceeding the threshold payload size, the proxyservers 312 may be configured to perform a division process that breaksthe payload of configuration items into smaller portions capable oftransmission on the communication channel(s). By dividing the payloadinto smaller portions that are below the threshold payload size, theproxy servers 312 may transfer each portion to one or more servers ofremote network management platform 320 until the entire payload iscompletely transmitted.

In some examples, in order to divide the payload into multiple portions,the proxy servers 312 may generate and utilize a graph that representsthe configuration items of the payload as nodes interconnected byunidirectional edges. The edges in the generated graph may representassociations between pairs of configuration items to which they connect.For example, an edge between two nodes may represent the associationthat exists between the pair of configuration items represented by thetwo nodes.

In some example embodiments, the associations between pairs ofconfigurations items may be classified either as weak associations orstrong associations. A weak association may represent a non-dependencyrelationship between a pair of configuration items. For example, awebserver may have weak associations to websites that operate via thewebserver since the webserver does rely upon any of the websites tooperate. By contrast, a strong association may represent a dependencyrelationship between a pair of configuration items. For example, thewebsites may have strong associations with the webserver since thewebsites require the webserver in order to operate. The proxy server mayuse the strength of associations when dividing the payload ofconfiguration items into multiple portions for a series oftransmissions.

After generating the graph depicting the associations between discoveredconfiguration items, the proxy servers 312 may divide the generatedgraph into overlapping sub-graphs based on associations represented bythe edges. For instance, a particular sub-graph may be populated byrecursively traversing and copying nodes and edges from the graph aslong as nodes in the particular sub-graph represent fewer configurationitems than the threshold payload size. By having a size less than thethreshold payload size, the configuration items represented by eachsub-graph may be transmitted using the communication channel(s) to theone or more server devices of remote network management platform 320.

In some examples, when determining sub-graphs based on the graph ofconfiguration items, each sub-graph may also require that for any firstnode with an outgoing edge representing a strong association to a secondnode, the second node is also included in the sub-graph. This way, thestrong associations between configuration items may be maintained withinsub-graphs and each configuration item that depends on anotherconfiguration item can be transmitted with that configuration items. Assuch, the sub-graphs might not depend on maintaining the weakassociations between configuration items in order to ensure that eachsub-graph represents an amount of configuration items that falls belowthe threshold payload size.

The resulting sub-graphs that are developed by dividing the graph mayeach represent a portion of the original payload of discoveredconfiguration items. As previously indicated, the division of the graphinto multiple sub-graphs enables the proxy servers 312 to transmit setsof configuration items as defined in each sub-graph to one or moreserver devices without the sets of configuration items exceeding thethreshold payload size. For instance, the proxy servers 312 may transmiteach portion of the payload in a sequential order until the completepayload of configuration items has been transmitted.

In a further example, multiple proxy servers 312 may simultaneouslytransmit different portions of the payload as defined by the sub-graphs.For instance, a first proxy server 312 may transmit a first portion ofthe payload as defined by one or more sub-graphs and a second proxyserver 312 may transmit a second portion of the payload as defined byone or more other sub-graphs. As a result, proxy servers 312 maytransmit the entire payload in an efficient manner.

In some examples, one or more proxy servers 312 may transmit portions ofthe payload to an external communication channel (ECC) queue thatcorresponds to a database table. Unlike other tables, in someimplementations, the ECC may be queried, updated, and inserted into byother systems (e.g., proxy servers 312). The ECC may further utilizereceived portions of the payload in various subsequent operations, suchas configuring or displaying the portions of the payload via clientdevices, etc.

In some examples, discovery of configuration items may involve scanningone or more patterns that help organize configuration items. A patternmay represent links between configurations items that were previouslydefined by a computing device or a user via a user-interface. Forexample, discovery of configuration items may involve scanning one ormore application patterns that link various applications in managednetwork 300. In turn, the discovery may produce a list of applicationsoperable in managed network 300 as well as associations between theapplications.

In another example, discovery of configuration items may involvescanning one or more infrastructure patterns that link hardwareoperating in managed network 300. For instance, an infrastructurepattern may specify associations between user devices and/or other typesof hardware. Discovery involving scanning infrastructure patterns mayproduce an inventory list of computing devices in managed network 300.

In some example embodiments, discovery may involve scanning multipletypes of patterns that exist between configuration items in managednetwork 300. For instance, discovery may involve scanning bothinfrastructure and application patterns.

FIG. 6A depicts a graph of discovered configuration items, in accordancewith example embodiments. As indicated above, one or more proxy servers312 (or another entity) may develop graph 600 subsequent to discoveringa payload of configuration items that exceeds a threshold payload sizelimiting transfer of the payload as a single transmission. Particularly,proxy servers 312 may generate graph 600 such that each node representsa discovered configuration item and the nodes are connected viaunidirectional edges that represent associations between pairs of nodes.Other configurations are possible.

Graph 600 includes host 602 represented as a node positioned at the topof graph 600. Host 602 may correspond to a network host that can provideinformation resources, services, and applications to computing devicesor other nodes in managed network 300. As such, managed network 300 mayinclude one or more hosts 602 in some examples. In other examples, thetop node or nodes in graph 600 may represent other types ofconfiguration items.

In addition to host 602, additional nodes in graph 600 representwebserver 604A and webserver 604B. Host 602 is connected to eachwebserver 604A, 604B via unidirectional edges that represent weakassociations 610 since host 602 does not depend on either webserver604A, 604B to operate. Accordingly, in some instances, a subsequentlydetermined sub-graph may include host 602 without either webservers604A, 604B included.

Additionally, edges representing strong associations 608 are shownextending from each webservers 604A, 604B to host 602. The edgesrepresenting strong associations 608 indicate that webservers 604A, 604Bmay depend on host 602 to operate within managed network 300.

Graph 600 further includes website 606A, website 606B, website 606C,website 606D, and website 606E represented as additional nodespositioned near the bottom of graph 600. Websites 606A-606E mayrepresent various websites or portals that operate within managednetwork 300. As such, websites 606A-606C are each shown connected towebserver 604A via strong associations 608 and websites 606D, 606E areeach shown connected webserver 604B via strong associations 608 sinceall websites 606A-606E depend on either webservers 604A, 604B to operatewithin managed network 300.

Conversely, webserver 604A is shown connected via weak associations 610to websites 606A, 606B, 606C, and webserver 604B is shown connected viaweak associations 610 to websites 606E, 606F. Webservers 604A, 604B haveweak associations 610 to websites 606A-606E since webservers 604A, 604Bgenerally do not depend on websites 606A-606E to operate.

FIG. 6B depicts a sub-graph formed based on the graph of discoveredconfiguration items, in accordance with example embodiments. Asdiscussed above, proxy servers 312 in managed network 300 may dividegraph 600 into overlapping sub-graphs (e.g., sub-graph 612) based on theassociations represented by the edges (e.g., strong associations 608,weak associations 610). Graph 600 may be divided into multiplesub-graphs in response to determining that the payload of discoveredconfiguration items represented in graph 600 exceeds a threshold payloadsize.

In some examples, sub-graph 612 as well as other sub-graphs developedbased on graph 600 may be populated by recursively traversing andcopying nodes and edges from graph 600 as long as nodes in sub-graph 612represent fewer configuration items than the threshold payload size. Forexample, when the threshold payload size limits transmissions to five orfewer configuration items, sub-graph 612 may be developed such that itincludes five or fewer configuration items. Other threshold payloadsizes can be used within examples. For instance, an example embodimentmay involve using a minimum threshold payload size and a maximumthreshold payload size for use during determination of the sub-graphs.The multiple thresholds may improve the efficiency of transferring alarge payload of configuration items.

In addition, when determining sub-graph 612 and other sub-graphs basedon graph 600, for any first node included in a particular sub-graph withan outgoing edge representing a strong association to a second node, thesecond node is also included in the particular sub-graph (e.g.,sub-graph 612). For example, sub-graph 612 may involve an initialselection of webserver 604A as a first node. Accordingly, when webserver604 is selected as the first node, host 602 may also be included sincewebserver 604A is linked to host 602 via a strong association 608 (i.e.,webserver 604A depends on host 602).

Additionally, websites 606A, 606B, 606C are shown included in sub-graph612. Although web server 604A does not depend on web sites 606A, 606B,606C, one or more of them may be included within the sub-graph 612depending on the limits set forth by the threshold payload size.

FIG. 6C depicts associations extending from a particular node in thesub-graph formed based on the graph of discovered configuration items,in accordance with example embodiments. The example provided in FIG. 6Cdepicts webserver 604A as the initially selected node for developingsub-graph 612 based on graph 600. As such, sub-graph further includesthe unidirectional edges representing associations that webserver 604Ahas with other nodes in graph 600.

As shown, host 602 is included in sub-graph 612 since webserver 604Adepends on host 602 to operate in managed network 300 as represented bystrong association 608. Thus, sub-graph 612 may include at least host602 and webserver 604A when webserver 604A is selected as the initialnode for determining sub-graph 612 based on graph 600.

In addition, FIG. 6C also shows weak associations 610 between webserver604A and websites 606A, 606B, 606C. In some instances, one or morewebsites 606A, 606B, 606C may be included in sub-graph 612 depending onthe limit placed on transmission sizes represented by the thresholdpayload size. For example, websites 606A, 606B, 606C may be includedwith webserver 604A and host 602 when the threshold payload size permitsthe transmission of at least five configuration items.

FIG. 6D depicts another sub-graph formed based on the graph ofdiscovered configuration items, in accordance with example embodiments.More specifically, sub-graph 614 represents a portion of theconfiguration items discovered and depicted in graph 600 in a examplescenario where the threshold payload size limits portions of the payloadto be transmitted with four or less configuration items. As shown,sub-graph 614 includes four configuration items, including host 602, webserver 604A, and websites 606A, 606B.

FIG. 6E depicts an additional sub-graph formed based on the graph ofdiscovered configuration items, in accordance with example embodiments.Sub-graph 616 represents another sub-graph formed based on graph 600 fortransmitting a portion of the payload of configuration items. Similar tosub-graph 614 depicted in FIG. 6C, sub-graph 616 includes webserver 604Aas the initial node as well as host 602, website 606C, and webserver604B.

In some examples, proxy servers 312 may determine sub-graph 614 andsub-graph 616 when dividing graph 600. As such, proxy servers 312 maytransmit both sub-graphs 614, 616 to server devices in remote networkmanagement platform 320. In a further example, an entity may scan andremove duplicate configuration items from sub-graphs 614, 616 to ensurethat multiple copies of the same configuration items are nottransmitted. In addition, in some examples, remote network managementplatform 320 may include one or more devices configured to removeduplicate configuration items received within sub-graphs from proxyservers 312.

FIG. 6F depicts an additional sub-graph formed based on the graph ofdiscovered configuration items, in accordance with example embodiments.Particularly, sub-graph 618 includes webserver 604B as the initiallyselected first node and further includes host 602 since webserver 604Bdepends on host 602 as represented by strong association 608.

In addition, sub-graph 618 also includes websites 606D, 606E since aportion of the payload that includes host 602, webserver 604B, andwebsites 606D, 606E is less than the example threshold payload size setforth for the example. In other examples, sub-graph 618 may include orless configuration items depending on the transmission limit representedby the threshold payload size.

FIG. 6G depicts a depth-first search of a portion of the graph ofdiscovered configuration items, in accordance with example embodiments.In particular, portion 620 of graph 600 includes host 602, webserver604A, website 606A, website 606B, and website 606C represented as nodes.Portion 620 also includes edges representing associations that extendfrom webserver 604A to other nodes.

When determining sub-graphs based on portion 620 of graph 600, proxyservers 312 may recursively traverse and copy nodes and edges fromportion 620 by conducting a depth-first search of portion 620. Adepth-first search may involve initially marking all nodes in portion620 as unvisited.

Proxy servers 312 may proceed with recursively traversing and copyingnodes and edges from portion 620 by marking any nodes that were copiedas visited. Proxy servers 312, however, may determine that a particularnode marked as visited has multiple incoming edges representing strongassociations, not all of which are included in a particular sub-graph.As a result, proxy servers 312 may include the particular node in theparticular sub-graph and in a subsequent sub-graph that contains theincoming edges representing strong associations that were not includedin the particular sub-graph. For instance, proxy servers 312 may markthe particular node as unvisited upon determining that the particularnode includes at least one incoming edge representative of a strongassociation that was not included within the particular sub-graph.

Portion 620 in FIG. 6G indicates an example depth-first search thatproxy servers or another entity may perform. Particularly, proxy servers312 may initially mark all nodes in portion 620 as unvisited. Whilerecursively traversing and copying nodes and edges from portion 620,proxy servers 312 may mark nodes copied into a sub-graph from portion620 as visited. For instance, in a scenario where the threshold payloadsize limits sub-graphs to four configuration items or less, proxyservers 312 may divide portion 620 into a first sub-graph that includeshost 602, webserver 604A, website 606A, and website 606B. Particularly,proxy servers 312 may select web server 604A as the initial node andmark the node as visited as indicated in step 1 of FIG. 6G.

Proxy servers 312 may also include host 602 in the first sub-graph sincewebserver 604A depends on host 602 as represented by strong association608. As such, as shown in FIG. G6, proxy servers 312 may mark host 602as visited as indicated by step 2. The first sub-graph may also includetwo more nodes (e.g., website 606A, website 606B) since the firstsub-graph can have up to four configuration items as indicated by thethreshold payload size used in the example scenario. Particularly, proxyservers 312 may mark web site 606A as visited for step 3 and markwebsite 606B as visited for step 4. As such, proxy servers 312 may markall nodes included within the first sub-graph as visited (i.e., allnodes aside from website 606C).

After compiling the first sub-graph, proxy servers 312 may determinethat webserver 604A marked as visited includes multiple incoming edgesrepresenting strong associations 608 including strong association 608from website 606C that was not included in the first sub-graph. As aresult, proxy servers 312 may include webserver 604A in the firstsub-graph and also in a second sub-graph that contains the incoming edgerepresenting strong association 608 from website 606C that was notincluded in the particular sub-graph. Particularly, step 5 shown in FIG.6G indicates that proxy servers 312 may mark webserver 604A asunvisited. Proxy servers 312 may also mark host 602 as unvisited forstep 6. As a result, proxy server 312 may generate a second sub-graphthat includes host 602, webserver 604A, and website 606C. In turn, thefirst sub-graph and the second sub-graph add together to include allnodes of portion 620. Other examples are possible.

In some examples, JavaScript Object Notation (JSON) can be used todiscover and describe configuration items identified in managed network300. For example, table 1 includes example JSON representations thatdescribe discovered configuration items, such as host 602, webserver604A, and website 606A. Particularly, the top JSON entry indicates thename, ip_address, the label used within managed network (i.e., host) andindicates that the entry is a configuration item (CI). The middle JSONentry represents information for the discovered webserver and the bottomJSON entry of table 1 represent information for the discovered website.

TABLE 1 “name”: “10.1.42.1:5959” “ip_address”: “”10.1.42.1”,“sys_class_name”: “host”, “discovery_descriptor”: “CI” “name”:“10.1.46.1:5875” “ip_address”: “”10.1.46.1”, “sys_class_name”:“webserver”, “discovery_descriptor”: “CI” “name”: “10.1.93.1:3257”“ip_address”: “”10.1.93.1”, “sys_class_name”: “website”,“discovery_descriptor”: “CI”

In addition, table 2 includes example JSON representations that describeassociations between the discovered configuration items in table 1.Particularly, each JSON entry connects JSON entries for configurationitems via IP addresses included above in table 1 and further indicatesthe strength of the association (i.e., strong or weak). As shown, thetop entry in table 2 represents the strong association extending fromthe webserver to the host. The second entry from the top represents theweak association extending from the host to the webserver. Similarly,the third and fourth entries represent the strong and weak associationsbetween the webserver and website.

TABLE 2 “link”: “10.1.46.1:5875 - 10.1.42.1:5959” “type”: “strong”“link”: “10.1.42.1:5959 - 10.1.46.1:5875 -” “type”: “weak” “link”:“10.1.46.1:5875 - 10.1.93.1:3257” “type”: “weak” “link”:“10.1.93.1:3257 - 10.1.46.1:5875 -” “type”: “strong”

VI. Example Operations

FIG. 7 is a flow chart illustrating an example embodiment. The processillustrated by FIG. 7 may be carried out by a computing device, such ascomputing device 100, and/or a cluster of computing devices, such asserver cluster 200 or proxy servers 312. However, the process can becarried out by other types of devices or device subsystems. For example,the process could be carried out by a portable computer, such as alaptop or a tablet device.

The embodiments of FIG. 7 may be simplified by the removal of any one ormore of the features shown therein. Further, these embodiments may becombined with features, aspects, and/or implementations of any of theprevious figures or otherwise described herein.

Block 702 may involve performing, by a proxy server application within amanaged network, a discovery process to identify configuration itemsrepresenting computing devices and applications. Particularly, themanaged network may include the computing devices configured to executethe applications.

In some examples, the discovery process may identify one or more of theconfiguration items via scanning one or more patterns representative ofassociations between configuration items in the managed network. Forinstance, the discovery process may involve scanning one or moreapplication patterns representative of associations between items in themanaged network to determine an inventory list of the applications inthe managed network. Similarly, the discovery process may also involvescanning one or more infrastructure patterns representative ofassociations between configuration items in the managed network todetermine an inventory list of the computing devices in the managednetwork.

Block 704 may involve determining that the configuration items exceed athreshold payload size. For instance, the threshold payload size mayrepresent a threshold quantity of configuration items that acommunication channel may transfer at a single time. As an example, thethreshold payload size may indicate that the communication channel(s)can transfer up to four configuration items at a time.

In some examples, the threshold payload size may be a multiple of anaverage configuration item size of the configuration items identifiedvia the discovery process. For example, to determine a portion of thepayload size, a system may determine the JavaScript Object Notation(JSON) size length of the payload of configuration items (e.g., stringlength). The system may divide the size length with the total items inthe payload to determine the average item size. Here, the associationsbetween the configuration items may not be used when determining theaverage configuration item size. To determine the total size of portionsof the payload, the system may multiple the items size by the determinedaverage item size.

Block 706 may involve, based on determining that the configuration itemsexceed the threshold payload size, generating a graph that representsthe configuration items as nodes interconnected by unidirectional edges.In particular, the edges may represent respective associations betweenpairs of configuration items to which they connect. The respectiveassociations are classified either as weak associations that representnon-dependency relationships between a respective pair of nodes or asstrong associations that represent dependency relationships between therespective pair of nodes.

In an example implementation, generation of the graph may involvecreating a graph object that contains the map of nodes. The system mayfurther run over all the associations between configuration items in thediscovered payload. For instance, the system may create nodes forconfiguration items and connect pairs of the nodes via edges based onthe associations between the configuration items.

In some examples, the system may utilize one or more previouslygenerated graphs, one or more database or service mappings, or otherrepresentations that convey strong and weak connections betweenconfiguration items. In a further example, the system may generate oneor more graphs along with utilizing one or more previously generatedgraphs or representations.

Block 708 may involve dividing the graph into overlapping sub-graphsbased on the respective associations represented by the edges. Aparticular sub-graph may be populated by recursively traversing andcopying nodes and edges from the graph as long as (i) nodes in theparticular sub-graph represent fewer configuration items than thethreshold payload size, and (ii) for any first node with an outgoingedge representing a strong association to a second node, the second nodeis in the sub-graph. For example, recursively traversing and copyingnodes and edges from the graph may involve conducting a depth-firstsearch of the graph. As a result, each sub-graph represents a portion ofa payload of the configuration items.

In some examples, all nodes in the graph may be initially marked asunvisited. As such, recursively traversing and copying nodes and edgesfrom the graph may involve marking copied nodes as visited anddetermining that a particular node marked as visited has multipleincoming edges representing strong associations, not all of which areincluded in the particular sub-graph. Recursively traversing and copyingnodes and edges from the graph may further involve marking theparticular node as unvisited and including the particular node in theparticular sub-graph and in a subsequent sub-graph. The subsequentsub-graph may contain the incoming edges representing strongassociations that were not included in the particular sub-graph.

Block 710 may involve separately transmitting, for each sub-graph and toone or more server devices, the configuration items defined therein. Theone or more server devices may be disposed within a remote networkmanagement platform that manages the managed network. As such, the oneor more server devices may be configured to obtain information regardingthe computing devices and the applications by way of the proxy serverapplication.

In a further example, a system may include means for splitting networkdiscovery payloads based on degree of relationships between nodes. Thesystem may include means for performing a discovery process to identifyconfiguration items representing computing devices and applications. Thecomputing devices and applications may operate within a managed network.

The system may also include means for determining that the configurationitems exceed a threshold payload size, and means for generating a graphthat represents the configuration items as nodes interconnected byunidirectional edges based on determining that the configuration itemsexceed the threshold payload size. In particular, the edges mayrepresent respective associations between pairs of configuration itemsto which they connect, and the respective associations are classifiedeither as weak associations that represent non-dependency relationshipsbetween a respective pair of nodes or as strong associations thatrepresent dependency relationships between the respective pair of nodes.

The system may also include means for dividing the graph intooverlapping sub-graphs based on the respective associations representedby the edges. A particular sub-graph may be populated by recursivelytraversing and copying nodes and edges from the graph as long as (i)nodes in the particular sub-graph represent fewer configuration itemsthan the threshold payload size, and (ii) for any first node with anoutgoing edge representing a strong association to a second node, thesecond node is in the sub-graph. As a result, each sub-graph representsa portion of a payload of the configuration items.

The system may also include means for separately transmitting, for eachsub-graph and to one or more server devices, the configuration itemsdefined therein. Particularly, the one or more server devices may bedisposed within a remote network management platform that manages themanaged network, and the one or more server devices may be configured toobtain information regarding the computing devices and the applicationsby way of the proxy server application.

VII. CONCLUSION

The present disclosure is not to be limited in terms of the particularembodiments described in this application, which are intended asillustrations of various aspects. Many modifications and variations canbe made without departing from its scope, as will be apparent to thoseskilled in the art. Functionally equivalent methods and apparatuseswithin the scope of the disclosure, in addition to those describedherein, will be apparent to those skilled in the art from the foregoingdescriptions. Such modifications and variations are intended to fallwithin the scope of the appended claims.

The above detailed description describes various features and operationsof the disclosed systems, devices, and methods with reference to theaccompanying figures. The example embodiments described herein and inthe figures are not meant to be limiting. Other embodiments can beutilized, and other changes can be made, without departing from thescope of the subject matter presented herein. It will be readilyunderstood that the aspects of the present disclosure, as generallydescribed herein, and illustrated in the figures, can be arranged,substituted, combined, separated, and designed in a wide variety ofdifferent configurations.

With respect to any or all of the message flow diagrams, scenarios, andflow charts in the figures and as discussed herein, each step, block,and/or communication can represent a processing of information and/or atransmission of information in accordance with example embodiments.Alternative embodiments are included within the scope of these exampleembodiments. In these alternative embodiments, for example, operationsdescribed as steps, blocks, transmissions, communications, requests,responses, and/or messages can be executed out of order from that shownor discussed, including substantially concurrently or in reverse order,depending on the functionality involved. Further, more or fewer blocksand/or operations can be used with any of the message flow diagrams,scenarios, and flow charts discussed herein, and these message flowdiagrams, scenarios, and flow charts can be combined with one another,in part or in whole.

A step or block that represents a processing of information cancorrespond to circuitry that can be configured to perform the specificlogical functions of a herein-described method or technique.Alternatively or additionally, a step or block that represents aprocessing of information can correspond to a module, a segment, or aportion of program code (including related data). The program code caninclude one or more instructions executable by a processor forimplementing specific logical operations or actions in the method ortechnique. The program code and/or related data can be stored on anytype of computer readable medium such as a storage device including RAM,a disk drive, a solid state drive, or another storage medium.

The computer readable medium can also include non-transitory computerreadable media such as computer readable media that store data for shortperiods of time like register memory and processor cache. The computerreadable media can further include non-transitory computer readablemedia that store program code and/or data for longer periods of time.Thus, the computer readable media may include secondary or persistentlong term storage, like ROM, optical or magnetic disks, solid statedrives, compact-disc read only memory (CD-ROM), for example. Thecomputer readable media can also be any other volatile or non-volatilestorage systems. A computer readable medium can be considered a computerreadable storage medium, for example, or a tangible storage device.

Moreover, a step or block that represents one or more informationtransmissions can correspond to information transmissions betweensoftware and/or hardware modules in the same physical device. However,other information transmissions can be between software modules and/orhardware modules in different physical devices.

The particular arrangements shown in the figures should not be viewed aslimiting. It should be understood that other embodiments can includemore or less of each element shown in a given figure. Further, some ofthe illustrated elements can be combined or omitted. Yet further, anexample embodiment can include elements that are not illustrated in thefigures.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purpose ofillustration and are not intended to be limiting, with the true scopebeing indicated by the following claims.

What is claimed is:
 1. A system, comprising: a client device configured to run a proxy server application for a managed network, wherein the client device is configured to receive information associated with one more computing devices and one or more applications in the managed network, and wherein running the proxy server application causes the client device to perform operations comprising: performing a discovery process to identify configuration items representing the one or more computing devices and the one or more applications; determining that a payload of the configuration items exceeds a threshold quantity of configuration items; and transmitting, to one or more server devices, respective portions of the payload of the configuration items in response to determining that the payload exceeds the threshold quantity of configuration items, wherein each portion of the respective portions is associated with a sub-graph of a graph that represents the configuration items as nodes interconnected by unidirectional edges indicative of whether each pair of nodes has an operationally dependent relationship or an operationally independent relationship, and wherein the graph is divided into overlapping sub-graphs based on the operationally dependent relationship or the operationally independent relationship of each pair of nodes.
 2. The system of claim 1, wherein the operations comprise dividing the payload of the configuration items into the respective portions in response to determining that the payload of the configuration items exceeds the threshold quantity of configuration items.
 3. The system of claim 2, wherein dividing the payload of the configuration items into the respective portions comprises generating the graph and dividing the graph into the overlapping sub-graphs.
 4. The system of claim 1, wherein a particular overlapping sub-graph of the overlapping sub-graphs is populated by recursively traversing and copying one or more nodes and one or more edges from the graph.
 5. The system of claim 4, wherein the one or more nodes in the particular overlapping sub-graph represents fewer configuration items than the threshold quantity of configuration items.
 6. The system of claim 4, wherein a first node of the particular overlapping sub-graph has an outgoing edge representing an operationally dependent relationship to a second node, and the second node is included in the particular overlapping sub-graph.
 7. The system of claim 1, wherein the respective portions of the payload of configuration items are separately transmitted to the one or more server devices.
 8. A method, comprising: performing a discovery process to identify configuration items representing one or more computing devices and one or more applications in a managed network; determining that a payload of the configuration items exceeds a threshold quantity of configuration items; and transmitting, to one or more server devices, respective portions of the payload of the configuration items in response to determining that the payload exceeds the threshold quantity of configuration items, wherein each portion of the respective portions is associated with a sub-graph of a graph that represents the configuration items as nodes interconnected by unidirectional edges indicative of whether each pair of nodes has an operationally dependent relationship or an operationally independent relationship, and wherein the graph is divided into overlapping sub-graphs based on the operationally dependent relationship or the operationally independent relationship of each pair of nodes.
 9. The method of claim 8, wherein the operations comprise dividing the payload of the configuration items into the respective portions in response to determining that the payload of the configuration items exceeds the threshold quantity of configuration items.
 10. The method of claim 9, wherein dividing the payload of the configuration items into the respective portions comprises generating the graph and dividing the graph into the overlapping sub-graphs.
 11. The method of claim 8, wherein a particular overlapping sub-graph of the overlapping sub-graphs is populated by recursively traversing and copying one or more nodes and one or more edges from the graph.
 12. The method of claim 11, wherein the one or more nodes in the particular overlapping sub-graph represents fewer configuration items than the threshold quantity of configuration items and represents more configuration items than a minimum threshold quantity of configuration items.
 13. The method of claim 11, wherein a first node of the particular overlapping sub-graph has an outgoing edge representing an operationally dependent relationship to a second node, and the second node is included in the particular overlapping sub-graph.
 14. The method of claim 8, comprising removing one or more nodes from two or more overlapping sub-graphs of the overlapping sub-graphs before separately transmitting the respective portions of the payload of the configuration items, wherein the one or more nodes represent respective duplicate configuration items.
 15. A non-transitory, computer-readable medium, comprising instructions that when executed by one or more processors, cause the one or more processors to perform operations comprising: performing a discovery process to identify configuration items representing one or more computing devices and one or more applications in a managed network; determining that a payload of the configuration items exceeds a threshold quantity of configuration items; dividing the payload of the configuration items into respective portions in response to determining that the payload of the configuration items exceeds the threshold quality of configuration items; and transmitting, to one or more server devices, the respective portions of the payload of the configuration items in response to determining that the payload exceeds the threshold quantity of configuration items, wherein each portion of the respective portions is associated with a sub-graph of a graph that represents the configuration items as nodes interconnected by unidirectional edges indicative of whether each pair of nodes has an operationally dependent relationship or an operationally independent relationship, and wherein the graph is divided into overlapping sub-graphs based on the operationally dependent relationship or the operationally independent relationship of each pair of nodes.
 16. The non-transitory, computer-readable medium of claim 15, wherein dividing the payload of the configuration items into the respective portions comprises generating the graph and dividing the graph into the overlapping sub-graphs.
 17. The non-transitory, computer-readable medium of claim 15, wherein the threshold quantity of configuration items is a multiple of an average configuration item size of the configuration items identified via the discovery process.
 18. The non-transitory, computer-readable medium of claim 15, wherein a particular overlapping sub-graph of the overlapping sub-graphs is populated by recursively traversing and copying one or more nodes and one or more edges from the graph.
 19. The non-transitory, computer-readable medium of claim 18, wherein a first node of the particular overlapping sub-graph has an outgoing edge representing an operationally dependent relationship to a second node, and the second node is included in the particular overlapping sub-graph.
 20. The non-transitory, computer-readable medium of claim 15, wherein the respective portions of the payload of configuration items are separately and simultaneously transmitted to the one or more server devices. 